ObjectiveThis study aimed to investigate the action mechanism by which Banxia Xiexintang （BXT） inhibits epithelial-mesenchymal transition （EMT） in chronic atrophic gastritis （CAG） rats by regulating the interleukin-17（IL-17）/extracellular regulated protein kinases（ERK）/CCAAT enhancer binding protein β（C/EBPβ）signaling pathway， thereby providing new theoretical evidence for the treatment of CAG with classic traditional Chinese medicine formulas. MethodsA CAG rat model was established by using the combined factor method. After successful modeling， the rats were randomly divided into the model group， low-， medium-， and high-dose groups （0.549， 1.098， 2.196 g·kg^-1， respectively） of BXT， and the positive drug group （vitacoenzyme， 0.3 g·kg^-1）. A normal control group was also set up. After 8 weeks of intervention， the pathological changes of gastric tissue were evaluated. The enzyme-linked immunosorbent assay （ELISA） was used to detect the contents of IL-17， tumor necrosis factor-α （TNF-α）， cyclooxygenase-2 （COX-2）， and C/EBPβ in serum， as well as the contents of EMT markers in gastric mucosal tissue including E-cadherin， N-cadherin， and vimentin. The immunohistochemistry method was employed to determine the localization and protein expression levels of IL-17， p-ERK， and C/EBPβ in gastric mucosal tissue. Western blot was used to detect the protein expressions of C/EBPβ， ERK， and its phosphorylated form （p）-ERK in gastric mucosa. Real-time polymerase chain reaction （Real-time PCR） was applied to measure the mRNA expression levels of ERK， COX-2， and C/EBPβ in gastric mucosa. ResultsCompared with those in the normal control group， the rats in the model group showed gastric mucosal glandular atrophy and inflammatory cell infiltration. The protein and their related mRNA expressions of C/EBPβ， ERK， and p-ERK in gastric mucosa were significantly increased （P<0.05，P<0.01）. The levels of IL-17， TNF-α， COX-2， and C/EBPβ in serum were significantly increased （P<0.01）. The contents of N-cadherin and vimentin in gastric mucosal tissue were significantly increased， while the content of E-cadherin was significantly decreased （P<0.01）. Compared with the model group， after intervention with different doses of BXT， the pathological damage of the gastric mucosa was improved to varying degrees. The protein and mRNA expressions of C/EBPβ， ERK， and p-ERK in gastric mucosa were significantly reduced （P<0.05，P<0.01）. The levels of IL-17， TNF-α， COX-2， and C/EBP β in serum were significantly decreased （P<0.01）. The contents of N-cadherin and vimentin in gastric mucosa tissue were decreased， while the content of E-cadherin was increased （P<0.05，P<0.01）. ConclusionBXT can effectively improve the pathological damage of gastric mucosal tissue in CAG rats. Its action mechanism may be related to reducing the levels of IL-17 and TNF-α in serum， regulating the IL-17/ERK/C/EBPβ signaling pathway and inhibiting the EMT process.

OBJECTIVE To prepare an intelligent responsive liposome-hydrogel nanopreparation co-loaded with gambogic acid （GA）， and characterize its antitumor activity in vitro . METHODS GA-ICG-Lip-gel was prepared by ethanol injection and cold dissolution， incorporating GA and the photosensitizer indocyanine green （ICG）. The appearance and microscopic morphology of GA-ICG-Lip-gel were observed， its encapsulation efficiency and drug loading capacity were measured， and its photothermal conversion performance， photothermal stability， and infrared imaging properties were investigated， along with the determination of its in vitro release profile. Human breast cancer MCF-7 cells were used as objects to investigate the effects of GA-ICG-Lip-gel （or with near-infrared light irradiation） on cell viability， migration ability， and the cellular uptake capacity of GA-ICG-Lip-gel. RESULTS GA-ICG-Lip-gel existed in a solution state at room temperature and transformed into a gel state at 37 ℃. Its microstructure was dense with small pores， and its encapsulation efficiency and drug loading were （96.07±0.86） % and （6.28±1.16） %， respectively. After exposure to near-infrared light， the temperature of GA-ICG-Lip-gel rose above 42 ℃， with no significant attenuation observed in the heating curve. The heating efficiency was dependent on both the irradiation time and drug concentration. Compared to media without gelatinase， the cumulative release rate of GA-ICG-Lip-gel increased in media containing gelatinase. In vitro studies showed that GA-ICG-Lip-gel could be efficiently taken up by MCF-7 cells； GA-ICG-Lip-gel significantly inhibited the viability and migration ability of MCF-7 cells （ P ＜0.05）， and this inhibitory effect was further enhanced under near-infrared light irradiation. CONCLUSIONS This study successfully prepares GA-ICG-Lip-gel， which exhibits favorable photothermal conversion properties and temperature/enzyme dual-responsive drug release characteristics， and demonstrates significant inhibitory effects on the proliferation and migration of breast cancer cells.

Objective To analyze the main causes and risk factors of unplanned reoperation after liver transplantation. Methods The clinical data of 242 liver transplant recipients in the First Affiliated Hospital of Anhui Medical University from January 2015 to December 2024 were retrospectively analyzed. According to whether unplanned reoperation was performed during the same hospitalization after surgery, the recipients were divided into the reoperation group (n=36) and the non-reoperation group (n=206). The preoperative, intraoperative and postoperative data of the two groups, as well as donor and graft-related data, were compared to analyze the risk factors of unplanned reoperation after liver transplantation and the survival status of the two groups. Results Among the 242 liver transplant recipients, 36 underwent unplanned reoperations, with a total of 54 procedures including various laparotomies, endoscopic and interventional surgeries, among which there were 20 laparotomies, 18 endoscopic surgeries and 16 interventional surgeries. The most common cause of unplanned reoperation was biliary complications (20 times), followed by vascular complications (17 times). Compared with the non-reoperation group, the reoperation group had longer graft cold ischemia time, higher postoperative fatality rate of recipients, longer length of stay in the intensive care unit and postoperative hospital stay, and higher total hospitalization costs (all P<0.05). The incidence of unplanned reoperation was higher in recipients who underwent split liver transplantation (P<0.05). Multivariate analysis showed that intraoperative blood loss ≥1 000 mL, positive culture of graft perfusate and split liver transplantation were independent risk factors for unplanned reoperation (all P<0.05). The postoperative 7-day, 1-month, 3-month and 6-month survival rates of recipients in the reoperation group and the non-reoperation group were 100% vs. 98.1%, 88.9% vs. 94.2%, 69.4% vs. 90.8% and 66.7% vs. 90.8%, respectively, and the postoperative survival rate of recipients in the reoperation group was lower than that in the non-reoperation group (P<0.05). Conclusions The main causes of unplanned reoperation after liver transplantation are biliary complications, vascular complications, abdominal incision infection and intra-abdominal hemorrhage. Intraoperative massive blood loss, positive culture of graft perfusate and split liver transplantation are the risk factors associated with unplanned reoperation after liver transplantation.

ObjectiveTo investigate the association between immunoglobulin G （IgG）/immunoglobulin M （IgM） ratio and prognosis in patients with initially unresectable hepatocellular carcinoma （iuHCC） receiving TTP triple therapy with transcatheter arterial chemoembolization （TACE）， tyrosine kinase inhibitor （TKI）， and programmed cell death protein-1 （PD-1） inhibitors. MethodsA retrospective analysis was performed for the clinical data of 151 iuHCC patients who received TTP triple therapy in Department of Hepatobiliary Surgery， Guangxi Medical University Cancer Hospital， from November 2019 to December 2022， and according to IgG/IgM ratio， they were divided into high IgG/IgM group （IgG/IgM ratio >13.23） and low IgG/IgM group （IgG/IgM ratio ≤13.23）. The t-test was used for comparison of continuous data between groups， and the chi-square test was used for comparison of categorical data between groups. The Kaplan-Meier method and the log-rank test were used for survival analysis， and the Cox proportional hazards model was used to investigate the potential influencing factors for overall survival （OS）. ResultsThe 151 patients had a median OS of 26.7 months （95% confidence interval ［CI］： 19.8-not reached） and a median progression-free survival of 12.5 months （95%CI： 10.4 — 15.8）. The objective response rate was 83.4% and the disease control rate was 94.0%. There were no significant differences in baseline data between the high IgG/IgM group and the low IgG/IgM group （all P>0.05）. There was a significant difference in median OS between the high IgG/IgM group and the low IgG/IgM group （20.6 months vs not reached， P=0.016）. In both the high IgG/IgM group and the low IgG/IgM group， salvage hepatectomy was significantly associated with the improvement in OS （χ²=8.297 and 10.307， both P<0.05）. The multivariate analysis showed that high IgG/IgM ratio （hazard ratio ［HR］=1.799， 95%CI： 1.077 — 3.006， P=0.025）， baseline alpha-fetoprotein >400 ng/mL （HR=1.762， 95%CI： 1.017 — 3.050， P=0.043）， and BCLC stage （HR=2.265， 95%CI： 1.212 — 4.232， P=0.010） were independent influencing factors for OS. ConclusionHigh IgG/IgM ratio is associated with a poorer prognosis in iuHCC patients receiving TTP triple therapy， and salvage hepatectomy has a potential value in improving the prognosis of patients with a high IgG/IGM ratio.

Tetrodotoxin（TTX）is a potent neurotoxin known for its specific sodium channel blocking effects, widely used in biomedical research. While TTX has been identified in various marine organisms, its true origin remains unclear, and the specific biosynthetic pathways are yet to be elucidated. The reported sources of TTX and the progress in research on TTX biosynthesis were summarized, with a focus on potential microbial sources of TTX, which could provide scientific reference for the production and biosynthesis studies of TTX.

The initiation of adaptive immune responses relies on the precise recognition and interpretation of antigenic information. In this process, the specific binding of T cell receptors (TCRs) to peptide-major histocompatibility complex (pMHC) molecules represents one of the key molecular events in the initiation of adaptive immune responses. Accordingly, the structural features of TCR-pMHC complexes provide a fundamental basis for dissecting antigen recognition mechanisms and support rational vaccine design, therapeutic target discovery in TCR-based immunotherapy, and TCR identification and optimization. However, experimental determination of TCR-pMHC structures remains costly, time-consuming, and limited in coverage, making computational approaches essential for rapidly obtaining reliable structural information. Computational methods for predicting the structures of TCR-pMHC complexes have advanced rapidly in recent years, driven by progress in deep learning-based modeling frameworks and the increasing availability of structural and sequence resources. Despite these developments, most existing tools do not adequately distinguish the key structural and biophysical differences between MHC class I (MHC-I) and MHC class II (MHC-II) complexes during model construction. As a consequence, their predictive performance differs substantially between class I and class II complexes. In general, structural predictions for class I complexes outperform those for class II complexes. This discrepancy may be related to several fundamental differences between the two systems, including the architecture of the peptide-binding groove, the distribution of peptide lengths, and the properties of peptide flanking residues (PFRs). Compared with MHC-I molecules, MHC-II molecules usually bind longer antigenic peptides, which typically range from 13 to 25 amino acids in length. PFRs at both termini of these peptides participate in regulating the overall conformation of TCR-pMHC class II complexes and exert a pronounced effect on the geometric and physicochemical characteristics of the TCR-pMHC binding interface. Furthermore, within the TCR recognition interface, the complementarity-determining regions (CDRs) consist of segments that differ markedly in conformational behavior. They commonly include regions that are relatively rigid and structurally stable, together with highly flexible segments exhibiting substantial conformational plasticity. These rigidity-flexibility features constitute an essential structural basis enabling TCRs to recognize diverse peptide-MHC ligands and to accommodate conformational heterogeneity at the interface. However, many current modeling tools, in an effort to enforce global conformational stability or reduce structural noise, tend to over-constrain intrinsically flexible regions. Such oversimplification may lead to inappropriate rigidification of flexible CDR loops, resulting in local structural distortions, compromised interface geometry, or even complete modeling failure for specific complexes. Against this background, the review approaches the field from the perspective of computational differences between MHC-I and MHC-II complexes. We first systematically organize and summarize available resources related to TCRs and pMHCs, including structural datasets, sequence databases, prediction tools, and benchmarking studies. We then focus on five representative tools capable of predicting both class I and class II complexes—AlphaFold2, AlphaFold3, TCRmodel2, tFold-TCR, and TCR-pHLA_ModellerS. After excluding structures present in the training sets of these tools, we constructed a benchmark dataset comprising 25 class I and 10 class II TCR-pMHC complexes in the bound state and conducted a systematic evaluation using this dataset. We first employ widely used general evaluation metrics, including All-Atom Root Mean Square Deviation (All-Atom RMSD), Backbone RMSD, Template Modeling score (TM-score), and DockQ, to assess the global conformational accuracy and interface modeling quality of class I and class II complexes. For class II complexes, we propose for the first time a peptide flanking residue deviation index, including the PFRs-Deviation Index (PFRs-DI), N-PFR-Deviation Index (N-PFR-DI), and C-PFR-Deviation Index (C-PFR-DI), to quantitatively characterize conformational deviations in PFRs. In addition, we propose the CDR conformational consistency index (CCC) designed to qualitatively evaluate the ability of prediction tools to capture TCR CDR conformational flexibility. These metrics collectively assess a tool’s ability to model both overall conformation and critical functional regions, thereby addressing the limitations of existing evaluation criteria that overemphasize global structure while inadequately capturing modeling quality in key functional areas. This establishes a unified analytical framework for MHC-I and MHC-II complexes to guide data resource selection, modeling strategy formulation, and evaluation system development. The framework further advances computational modeling and provides crucial support for multi-scale analysis of TCR-pMHC recognition mechanisms and their biological functions.

ObjectiveTo analyze the epidemiological characteristics of a local dengue fever cluster outbreak in Qingpu District of Shanghai in 2024, and to provide a reference for subsequent dengue fever prevention and control. MethodsSeven confirmed local dengue fever cases reported through the National Notifiable Infectious Diseases Surveillance System in Qingpu District of Shanghai in 2024 were selected as the research subjects. Descriptive epidemiological methods were used to conduct investigation and analysis from the aspects of onset, medical treatment and reporting, clinical symptoms, travel and contact history within 15 days before onset, and activity trajectories. ResultsA total of 7 cases were identified in this outbreak. None of the cases had a travel history to dengue-endemic areas within 15 days prior to onset, while all had shared exposure environments and mosquito bite histories, indicating a local clustered transmission pattern. The main clinical manifestations included fever (100.00%) and myalgia (42.86%). All 7 cases were positive for dengue virus serotype 2 (DENV-2) by nucleic acid testing. Genetic sequencing showed that the virus strains belonged to the Cosmopolitan genotype and were most closely related to the epidemic DENV strains circulating in southern China in recent years. ConclusionThis outbreak might be a local secondary infection caused by the short-term stay of dengue fever-infected individuals, and the possible source of importation was dengue fever endemic areas in southern China.

The initiation of adaptive immune responses relies on the precise recognition and interpretation of antigenic information. In this process, the specific binding of T cell receptors (TCRs) to peptide-major histocompatibility complex (pMHC) molecules represents one of the key molecular events in the initiation of adaptive immune responses. Accordingly, the structural features of TCR-pMHC complexes provide a fundamental basis for dissecting antigen recognition mechanisms and support rational vaccine design, therapeutic target discovery in TCR-based immunotherapy, and TCR identification and optimization. However, experimental determination of TCR-pMHC structures remains costly, time-consuming, and limited in coverage, making computational approaches essential for rapidly obtaining reliable structural information. Computational methods for predicting the structures of TCR-pMHC complexes have advanced rapidly in recent years, driven by progress in deep learning-based modeling frameworks and the increasing availability of structural and sequence resources. Despite these developments, most existing tools do not adequately distinguish the key structural and biophysical differences between MHC class I (MHC-I) and MHC class II (MHC-II) complexes during model construction. As a consequence, their predictive performance differs substantially between class I and class II complexes. In general, structural predictions for class I complexes outperform those for class II complexes. This discrepancy may be related to several fundamental differences between the two systems, including the architecture of the peptide-binding groove, the distribution of peptide lengths, and the properties of peptide flanking residues (PFRs). Compared with MHC-I molecules, MHC-II molecules usually bind longer antigenic peptides, which typically range from 13 to 25 amino acids in length. PFRs at both termini of these peptides participate in regulating the overall conformation of TCR-pMHC class II complexes and exert a pronounced effect on the geometric and physicochemical characteristics of the TCR-pMHC binding interface. Furthermore, within the TCR recognition interface, the complementarity-determining regions (CDRs) consist of segments that differ markedly in conformational behavior. They commonly include regions that are relatively rigid and structurally stable, together with highly flexible segments exhibiting substantial conformational plasticity. These rigidity-flexibility features constitute an essential structural basis enabling TCRs to recognize diverse peptide-MHC ligands and to accommodate conformational heterogeneity at the interface. However, many current modeling tools, in an effort to enforce global conformational stability or reduce structural noise, tend to over-constrain intrinsically flexible regions. Such oversimplification may lead to inappropriate rigidification of flexible CDR loops, resulting in local structural distortions, compromised interface geometry, or even complete modeling failure for specific complexes. Against this background, the review approaches the field from the perspective of computational differences between MHC-I and MHC-II complexes. We first systematically organize and summarize available resources related to TCRs and pMHCs, including structural datasets, sequence databases, prediction tools, and benchmarking studies. We then focus on five representative tools capable of predicting both class I and class II complexes—AlphaFold2, AlphaFold3, TCRmodel2, tFold-TCR, and TCR-pHLA_ModellerS. After excluding structures present in the training sets of these tools, we constructed a benchmark dataset comprising 25 class I and 10 class II TCR-pMHC complexes in the bound state and conducted a systematic evaluation using this dataset. We first employ widely used general evaluation metrics, including All-Atom Root Mean Square Deviation (All-Atom RMSD), Backbone RMSD, Template Modeling score (TM-score), and DockQ, to assess the global conformational accuracy and interface modeling quality of class I and class II complexes. For class II complexes, we propose for the first time a peptide flanking residue deviation index, including the PFRs-Deviation Index (PFRs-DI), N-PFR-Deviation Index (N-PFR-DI), and C-PFR-Deviation Index (C-PFR-DI), to quantitatively characterize conformational deviations in PFRs. In addition, we propose the CDR conformational consistency index (CCC) designed to qualitatively evaluate the ability of prediction tools to capture TCR CDR conformational flexibility. These metrics collectively assess a tool’s ability to model both overall conformation and critical functional regions, thereby addressing the limitations of existing evaluation criteria that overemphasize global structure while inadequately capturing modeling quality in key functional areas. This establishes a unified analytical framework for MHC-I and MHC-II complexes to guide data resource selection, modeling strategy formulation, and evaluation system development. The framework further advances computational modeling and provides crucial support for multi-scale analysis of TCR-pMHC recognition mechanisms and their biological functions.

Background: Adrenocortical hormones, particularly 11-oxygenated androgens, are pivotal in female reproductive health and fertility. Standardized detection kits and population-specific reference intervals are lacking in China, hindering related clinical applications. Methods: A HPLC-tandem mass spectrometry (HPLC-MS/MS) pipeline was developed, rigorously validated, and applied to simultaneously quantify corticosterone, cortisone, cortisol, 18-OH cortisol, androstenedione (A4), 11β-hydroxyandrostenedione (11-OH A4), dehydroepiandrosterone, and dehydroepiandrosterone sulfate in serum samples from 455 reproductive-aged women (18–45 yrs) in Guangxi, China. Age-dependent concentration trends were analyzed, and reference intervals stratified by age (2.5th to 97.5th percentiles) were established. Correlations with body-composition metrics, ethnicity, and the menstrual cycle were investigated. Results: The HPLC-MS/MS method demonstrated high precision (intra- and inter-assay CVs < 15%), accuracy, and sensitivity. All eight hormones exhibited significant age-related declines (P < 0.001 for seven hormones; P = 0.001 for 11-OH A4). Notably, 11-OH A4 levels were significantly lower in the 35–45-yr (3.05 nmol/L) and 25–34-yr (3.09 nmol/L) age groups than in the 18–24-yr (3.57 nmol/L) age group, whereas no significant difference was observed between the 35–45-yr and 25–34-yr age groups. Weak negative correlations were observed between the body mass index and corticosterone and cortisone levels, whereas ethnicity and the menstrual cycle showed no significant associations with hormone levels. Conclusions We developed an HPLC-MS/MS-based method for simultaneously quantifying eight adrenocortical hormones, including 11-OH A4, and defined age-specific reference intervals for reproductive-aged Chinese women. These findings advance the clinical utility of adrenocortical hormones in diagnosing and managing reproductive disorders.

Background: Cerebral hypoxia-ischemia impairs brain development in extremely preterm infants and is associated with poor neurological outcomes. Near-infrared spectroscopy (NIRS) is a noninvasive continuous monitoring method for regional cerebral oxygen saturation (rcSO2).Purpose: This study evaluated the clinical feasibility and neurological impact of a neurocritical care bundle that incorporates prolonged multidisciplinary hemodynamic monitoring and a stepwise management algorithm. Methods: Preterm infants with a gestational age (GA) ≤28 weeks or birth weight (BW) ≤1,000 g were prospectively enrolled in a bundle group subjected to NIRS for rcSO2, electrical cardiometry for cardiac output, and daily brain and cardiac echography during the first 72 hours of life. Monitoring was repeated weekly in the first month and then monthly until discharge or the term-equivalent age (TEA) was reached. We implemented a stepwise management algorithm for treating cerebral hypoxia. The primary outcome was a composite of mortality and adverse neurological events (structural abnormalities or electroencephalogram-confirmed seizures) before discharge. The secondary outcomes were the physiological pattern of rcSO2 within the initial 72 hours and up to discharge or TEA. Results: Thirty preterm infants (GA, 27.1±2.0 weeks; BW, 830±225 g) were enrolled in the bundle group. The mean time-averaged rcSO2 (66.8%±10.3%) was not associated with GA or BW. However, postnatal age appeared to influence physiological rcSO2 changes, given that rcSO2 values were higher during the initial 72 hours than at subsequent intervals. Seven infants (23.3%) had poor outcomes and significantly lower time-averaged rcSO2 (51.1% [50.0%–65.2%] vs. 71.8% [67.1%–73.1%], P=0.002). Multivariate regression indicated that a lower rcSO2 was an independent risk factor, and a 65% threshold showed an optimal predictive value for poor outcomes. Conclusion The neurocritical care bundle helped identify preterm infants at risk of cerebral hypoxia, and lower rcSO2 was an independent risk factor for composite mortality and adverse neurological outcomes.